低嗜酸性粒细胞及其动态变化作为感染患者死亡预测因子的系统综述与meta分析

数据集获取（Figshare）

• 源站标题：Low eosinophils and their dynamic as a predictor of death in patients with infections: a systematic review and meta-analysis of cohort studies
• DOI：10.6084/m9.figshare.29835636.v1
• 发布日期：2025-08-06
• 文件数：2 个
• 文件总体积：6.73 MB
• 源站页面：https://tandf.figshare.com/articles/dataset/Low_eosinophils_and_their_dynamic_as_a_predictor_of_death_in_patients_with_infections_a_systematic_review_and_meta-analysis_of_cohort_studies/29835636

命令行下载

curl -L -o "iann_a_2541084_sm5129.docx" "https://ndownloader.figshare.com/files/56938950"
curl -L -o "iann_a_2541084_sm5128.docx" "https://ndownloader.figshare.com/files/56938953"

文件清单

• iann_a_2541084_sm5129.docx（31.15 KB）
• iann_a_2541084_sm5128.docx（6.70 MB）

文件总体积 6.73 MB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Eosinophils prognostic significance in predicting mortality has become particularly notable during the COVID-19 pandemic. We aimed to evaluate the prognostic value of peripheral low eosinophil (eosinopenia) with focus on their dynamics (eosinophil recovery) in patients with infections.
We searched databases (MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library) and additional sources from inception to 1 December 2023. Cohort studies involving adult patients hospitalized with infections were evaluated using dual-reviewer methodology.
Out of 15,066 screened papers, 151 studies met the inclusion criteria, with 107 focused on COVID-19, 14 on sepsis, 9 on Clostridioides difficile, 6 on acute COPD exacerbations, and 17 on other infections. The majority of studies reported significantly lower admission eosinophil levels in non-survivors compared to survivors. Random-effects model meta-analysis showed mean eosinophil difference between deceased and survivors −15.31 (95% CI: −18.72 to −11.90) for COVID-19 and −44.6 (95% CI: −95.62 to 6.41) for sepsis (I2 > 90%). Mortality with eosinopenia showed low certainty of evidence for C. difficile (0 cells/mm³ cut-off: RR 2.35; 95% CI: 1.84–2.99) and very low for COVID-19 when considering different cut-offs (0 cells/mm³: RR 2.37; 95% CI: 1.86–3.01; 20 cells/mm³: RR 2.90; 95% CI: 1.59–5.28; 50 cells/mm³: RR 2.70; 95% CI: 1.33–5.49). Survivors generally showed an increase in eosinophil counts within the first 2–5 days of hospitalization, while the deceased had persistently low levels.
Eosinopenia, particularly the trajectory of eosinophil recovery, may serve as a cost-effective and accessible prognostic marker for mortality in patients with infections.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.29835636.v1（source: https://tandf.figshare.com/articles/dataset/Low_eosinophils_and_their_dynamic_as_a_predictor_of_death_in_patients_with_infections_a_systematic_review_and_meta-analysis_of_cohort_studies/29835636）。